Nanometer Positioning in the Presence of Friction

Abstract:

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This paper deals with nanometer positioning in the presence of friction. The object
studied is a ball-screw-driven and linear-ball-guide-supported table system. For this system, the
friction dominates the resulting performance for micro-motion and the system exhibits
microdynamic characteristic which is rather different from macrodynamics. Inherently a controller
with high loop-gain is needed to suppress the effect of friction. A PID controller is designed for the
table system for step height smaller than 10μm. Experiment and simulation results indicate that the
PID controller can provide a sufficiently high-loop gain and effect of friction is suppressed. In
point-to-point(PTP) positioning for step heights from 10μm down to 10nm, the positioning error is
within ±2 nm and the response dynamics is satisfactory.

Abstract: On the basis of sufficient analysis to the characteristic of iterative learning control and PID controller parameter tuning, an idea of applying iterative learning control to PID controller parameter tuning was aroused in this paper, we choose the linear model around the character point of Roll Attitude controller as the research plant, transforming the problem of PID controller parameter tuning into the problem of open-close loop iterative learning control problem. The stability of PID controller parameter iterative learning control system and the astringency of controller parameters were verified for the first time through the construct of a compress mapping arithmetic operator, and a novel stop condition design scheme of integral type is advanced at the same time, the iterative learning of PID controller parameter was then successfully solved. The ultimate simulation study validates the correctness and the effectiveness of the theory.

Abstract: This paper takes the layered water injection technology in oil production engineering as research object. This technology is characterized by strong nonlinearity, strong interlayer interference, time variation and complex model. Focusing on these characteristics, this paper proposes a novel control strategy based on PID-NN algorithm to satisfy the requirements of layered water injection technology. Many performance indexes of the controller are optimized, including model establishment of nonlinear controlled object, multi-parameter decoupling, controller acceleration and precision improvement. The simulation and experiment show that compared with traditional controller based on PID and controller based on BP neural network, the optimized controller has stronger robustness, faster response and better flow control, so it has an advantage over traditional controllers of dealing with discrete events and multi-variable decoupling problems.

Abstract: The digital PID controller system for magnetic bearing was described in this paper which combined Matlab technique with simulation of the magnetic bearing control to reach the influence of parameters of digital PID controller for magnetic bearing control system. The application of the expansion coefficient critical proportion for turning parameters of digital PID controller can achieve better results. Finally, provide a simple and efficient method for numerical controller of magnetic bearing.

Abstract: For the problem of that the traditional brushless DC torque motor controller position servo system is difficult to track accurately the complex and varied location information, an improved double closed-loop controller is designed in this paper. A self-adaptive PID algorithm based on RBF neural network is employed to design position loop controller and a feed-forward control algorithm is used in the speed loop controller. The improved double closed-loop controller validated the feasibility of the new method for the design of brushless DC torque motor position servo system

Abstract: The brushless DC motor (BLDCM) non-linear and the complexity of the working conditions are likely to cause the conventional PID servo control performance is not satisfactory. In order to improve the performance of the BLDCM servo control system and PID parameter tuning efficiency, this paper designs an adaptive fuzzy PID controller. Fuzzy logic PID controller parameters Kp, Ki, Kd are adjusted online real time to achieve the effect of optimal control, the BLDCM speed is as to the control object, and in the Matlab of Simulink toolbox simulation is used to achieve speed closed loop of BLDCM. According to comparative analysis of the conventional PID and adaptive fuzzy PID of Dynamic response curve, adaptive Fuzzy PID quick start for brushless DC motors, anti-disturbance has better control effect.